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What is SAS Text Miner?

SAS Text Miner facilitates the extraction of valuable insights from diverse text documents, uncovering hidden themes and concepts. This tool adeptly combines quantitative information with unstructured text, effectively blending text mining with traditional data mining techniques. Being a part of the SAS® Enterprise Miner suite, it requires that SAS Enterprise Miner is installed on the same system to function properly. Furthermore, SAS High-Performance Text Mining can run on both a grid of computers or a single machine with multiple CPUs, making it flexible for various computing environments. The text algorithms used are optimized for multi-threading and operate in memory, which greatly improves both speed and efficiency while reducing input/output load. Users can access SAS Text Miner as nodes within the SAS High-Performance Data Mining framework or through the procedures PROC HPTMINE and PROC HPTMSCORE. To better understand SAS technology, individuals can take advantage of training courses provided by analytics experts, which will help them attain a thorough grasp of the available tools. Gaining expertise in these areas not only boosts one’s analytical skills but also enhances overall capabilities in data mining and analysis methodologies. Ultimately, mastering these techniques can empower users to make more informed decisions based on data-driven insights.

What is Cauliflower?

Cauliflower is capable of processing feedback and comments related to all kinds of services or products. Utilizing Artificial Intelligence (AI), Cauliflower identifies key topics, assesses their significance, and establishes connections between them. It employs proprietary machine learning models designed to extract relevant content and gauge sentiment accurately. The platform features user-friendly dashboards equipped with filtering options and the ability to drill down into specific data points. Users can utilize various parameters to specify language, weight, ID, and timeframes. Additionally, custom filter variables can be defined from a dropdown menu. If needed, Cauliflower can translate its findings into a standardized language to ensure consistency. By adopting a company-wide language, businesses can move beyond sporadic readings of customer feedback and avoid simply quoting isolated opinions, thus fostering a more cohesive understanding of customer sentiment. This approach ultimately enhances strategic decision-making and improves overall customer engagement.

Media

Media

Integrations Supported

Integrations Supported

Amazon
Google Business Profile
Google Play
Tripadvisor
Trustpilot
Yelp

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Online Training

Company Facts

Organization Name

SAS Institute

Date Founded

1976

Company Location

United States

Company Website

support.sas.com/en/software/text-miner-support.html

Company Facts

Organization Name

Cauliflower

Date Founded

2019

Company Location

Germany

Company Website

www.cauliflower.ai/

Categories and Features

Text Analytics

Not specified

Text Mining

Boolean Queries
Document Filtering
Language Detection
Predictive Modeling
Sentiment Analysis
Taxonomy Classification
Topic Clustering

Categories and Features

Artificial Intelligence

For Healthcare
For eCommerce
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation

Customer Experience

Dashboard
Sentiment Analysis
Text Analysis

Data Analysis

Data Visualization
Predictive Analytics
Sentiment Analysis

Deep Learning

Document Classification
Self-Learning
Visualization

Machine Learning

Deep Learning
Natural Language Processing (NLP)
Predictive Modeling
Visualization

Qualitative Data Analysis

Data Visualization
Multi-Language
Sentiment Analysis
User Research Analysis

Text Analytics

Not specified

Text Mining

Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Text Analysis
Topic Clustering

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